System and method for processing medical claims using biometric signatures

ABSTRACT

A system for processing medical claims, comprising a processor configured to receive device-generated information from a medical device. The device-generated information includes performance information. The processor generates a first biometric signature, and using the device-generated information, generates a second biometric signature, wherein the second biometric signature uses the performance information. Using the first and second biometric signatures, the processor generates a signature comparison. Using the signature comparison, the processor generates a signature indicator and transmits the signature indicator.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/379,548, filed Jul. 19, 2021, titled “System and Method forProcessing Medical Claims Using Biometric Signatures,” which is acontinuation-in-part of U.S. patent application Ser. No. 17/021,895,filed Sep. 15, 2020, titled “Telemedicine for Orthopedic Treatment,”which claims priority to and the benefit of U.S. Provisional PatentApplication Ser. No. 62/910,232, filed Oct. 3, 2019, titled“Telemedicine for Orthopedic Treatment,” the entire disclosures of whichare hereby incorporated by reference for all purposes. U.S. patentapplication Ser. No. 17/379,548 further claims priority to and thebenefit of U.S. patent application Ser. No. 17/147,593, filed Jan. 13,2021, titled “System and Method for Processing Medical Claims UsingBiometric Signatures”, which claims priority to and the benefit of U.S.Provisional Patent Application Ser. No. 63/028,420, filed May 21, 2020,titled “System and Method for Processing Medical Claims Using BiometricSignatures,” the entire disclosure of which is hereby incorporated byreference for all purposes.

TECHNICAL FIELD

This disclosure relates generally to systems and methods for processingmedical claims using biometric signatures.

BACKGROUND

Electronic medical record (EMR) systems may be used to generate andmaintain an electronic record of health-related information relating toor about individuals within a health care organization. Thehealth-related information may be input by a variety of entities, e.g.,the individuals' health care providers, where such entries may be madeby any medically-related entity or its representatives, for example:administrators, nurses, doctors, or other authorized individuals;insurance companies; billing companies; hospitals; testing centers, suchas those related to radiologic services, blood and bodily fluid testingservices; and psychological service providers, such as psychologists,social workers, addiction and other counselors, and psychiatrists. Eachhealthcare service may have one or more medical billing codes, forexample, Diagnosis-Related Group (DRG) and/or InternationalClassification of Diseases (ICD) codes, e.g., ICD-10, assigned forbilling purposes. Some of the individual's EMRs, including the one ormore medical billing codes, may be transferred to a third-party payor,such as an insurance company, for invoicing the individual's medicalclaims for the individual's healthcare services. A medical claim, or aclaim, is a medical bill, or bill, submitted to a health insurancecarrier, or other party responsible for payment, for services renderedand/or goods provided to patients by health care providers. After amedical claim is submitted to the insurance company, the insurancecompany determines its financial responsibility for the payment to thehealthcare provider (i.e., claim adjudication). The insurance companymay have procedures to ensure that no false medical claims are approvedfor payment, for example, by rejecting payment for medical billing codesinconsistent with the healthcare services provided. As a result of suchprocedures, the insurance company may decide to pay the medical claim infull, reduce the medical bill, deny the full medical claim, or revisethe nature of the claim such that it becomes eligible for full orpartial payment.

Medical billing may present difficulties in claim adjudication whenusing medical billing codes, often making it difficult for insurancecompanies to detect whether a particular medical claim is the result offraud, waste, or abuse. Even if an insurance company has the ability todetermine that a medical device has been used, the insurance company mayhave difficulty in determining whether the use of that medical devicewas properly billed (e.g., the medical device was not used by or for thepatient stated in the medical claim). The use of telemedicine may resultin additional risks related to fraud, waste, and abuse, risks which badactors can exploit. For example, if, at a location other than ahealthcare facility, the medical device is being used, a healthcareprovider may not oversee the use (e.g., treatment, rehabilitation, ortesting), and therefore, the healthcare provider may not be able toeasily confirm or validate the accuracy of the medical billing.

SUMMARY

In general, the present disclosure provides a system and method forprocessing medical claims using biometric signatures.

An aspect of the disclosed embodiments includes a computer-implementedsystem for processing medical claims. The computer-implemented systemincludes a medical device configured to be manipulated by a user whilethe user performs a treatment plan; a patient interface associated withthe medical device, the patient interface comprising an outputconfigured to present telemedicine information associated with atelemedicine session; and a processor. The processor is configured to,during the telemedicine session, receive device-generated informationfrom the medical device; generate a first biometric signature; using thedevice-generated information, generate a second biometric signature;using the first and second biometric signatures, generate a signaturecomparison; using the signature comparison, generate a signatureindicator; and transmit the signature indicator.

An aspect of the disclosed embodiments includes a system for processingmedical claims. The system includes a processor configured to receivedevice-generated information from a medical device; to generate a firstbiometric signature; to use the device-generated information to generatea second biometric signature; to use the first biometric signature andthe second biometric signature to generate a signature comparison; touse the signature comparison to generate a signature indicator; and totransmit the signature indicator.

An aspect of the disclosed embodiments includes a method for processingmedical claims. The method includes receiving device-generatedinformation from a medical device. The method further includesgenerating a first biometric signature; using the device-generatedinformation to generate a second biometric signature; using the firstbiometric signature and the second biometric signature to generate asignature comparison; using the signature comparison to generate asignature indicator; and transmitting the signature indicator.

An aspect of the disclosed embodiments includes a tangible,non-transitory computer-readable storage medium. The tangible,non-transitory computer-readable storage medium stores instructionsthat, when executed, cause a processor to receive device-generatedinformation from a medical device. The instructions further cause aprocessor to generate a first biometric signature; to use thedevice-generated information to generate a second biometric signature;to use the first biometric signature and the second biometric signatureto generate a signature comparison; to use the signature comparison togenerate a signature indicator; and to cause the processor to transmitthe signature indicator.

Another aspect of the disclosed embodiments includes a system thatincludes a processing device and a memory communicatively coupled to theprocessing device and capable of storing instructions. The processingdevice executes the instructions to perform any of the methods,operations, or steps described herein.

Another aspect of the disclosed embodiments includes a tangible,non-transitory computer-readable medium storing instructions that, whenexecuted, cause a processing device to perform any of the methods,operations, or steps disclosed herein.

Other technical features may be readily apparent to one skilled in theart from the following figures, descriptions, and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of this disclosure and its advantages,reference is now made to the following description, taken in conjunctionwith the accompanying drawings. It is emphasized that, according tocommon practice, the various features of the drawings are not to-scale.On the contrary, the dimensions of the various features are arbitrarilyexpanded or reduced for clarity.

FIG. 1 generally illustrates a component diagram of an illustrativemedical system according to the principles of this disclosure.

FIG. 2 generally illustrates an example medical device according to theprinciples of this disclosure.

FIG. 3 generally illustrates a component diagram of an illustrativeclinic server system according to the principles of this disclosure.

FIG. 4 generally illustrates a component diagram and method of anillustrative medical claim processing system according to the principlesof this disclosure.

FIG. 5 generally illustrates a component diagram of an alternativearrangement of an illustrative medical claim processing system accordingto the principles of this disclosure.

FIGS. 6A and 6B generally illustrate a method of processing medicalclaims according to the principles of this disclosure.

FIG. 7 generally illustrates a perspective view of an embodiment of thedevice, such as a treatment device according to certain aspects of thisdisclosure.

FIG. 8 generally illustrates a perspective view of a pedal of thetreatment device of FIG. 7 according to certain aspects of thisdisclosure.

FIG. 9 generally illustrates a perspective view of a person using thetreatment device of FIG. 7 according to certain aspects of thisdisclosure.

FIG. 10 generally illustrates an example computer system according tocertain aspects of this disclosure.

NOTATION AND NOMENCLATURE

Various terms are used to refer to particular system components.Different companies may refer to a component by different names—thisdocument does not intend to distinguish between components that differin name but not function. In the following discussion and in the claims,the terms “including” and “comprising” are used in an open-endedfashion, and thus should be interpreted to mean “including, but notlimited to . . . .” Also, the term “couple” or “couples” is intended tomean either an indirect or direct connection. Thus, if a first devicecouples to a second device, that connection may be through a directconnection or through an indirect connection via other devices andconnections.

The terminology used herein is for the purpose of describing particularexample embodiments only, and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. The method steps, processes, and operations described hereinare not to be construed as necessarily requiring their performance inthe particular order discussed or illustrated, unless specificallyidentified as an order of performance. It is also to be understood thatadditional or alternative steps may be employed.

The terms first, second, third, etc. may be used herein to describevarious elements, components, regions, layers and/or sections; however,these elements, components, regions, layers and/or sections should notbe limited by these terms. These terms may be only used to distinguishone element, component, region, layer, or section from another region,layer, or section. Terms such as “first,” “second,” and other numericalterms, when used herein, do not imply a sequence or order unless clearlyindicated by the context. Thus, a first element, component, region,layer, or section discussed below could be termed a second element,component, region, layer, or section without departing from theteachings of the example embodiments. The phrase “at least one of,” whenused with a list of items, means that different combinations of one ormore of the listed items may be used, and only one item in the list maybe needed. For example, “at least one of: A, B, and C” includes any ofthe following combinations: A, B, C, A and B, A and C, B and C, and Aand B and C. In another example, the phrase “one or more” when used witha list of items means there may be one item or any suitable number ofitems exceeding one.

Spatially relative terms, such as “inner,” “outer,” “beneath,” “below,”“lower,” “above,” “upper,” “top,” “bottom,” “inside,” “outside,”“contained within,” “superimposing upon,” and the like, may be usedherein. These spatially relative terms can be used for ease ofdescription to describe one element's or feature's relationship toanother element(s) or feature(s) as illustrated in the figures. Thespatially relative terms may also be intended to encompass differentorientations of the device in use, or operation, in addition to theorientation depicted in the figures. For example, if the device in thefigures is turned over, elements described as “below” or “beneath” otherelements or features would then be oriented “above” the other elementsor features. Thus, the example term “below” can encompass both anorientation of above and below. The device may be otherwise oriented(rotated 90 degrees or at other orientations) and the spatially relativedescriptions used herein interpreted accordingly.

A “treatment plan” may include one or more treatment protocols, and eachtreatment protocol includes one or more treatment sessions. Eachtreatment session comprises several session periods, with each sessionperiod including a particular exercise for treating the body part of thepatient. For example, a treatment plan for post-operative rehabilitationafter a knee surgery may include an initial treatment protocol withtwice daily stretching sessions for the first 3 days after surgery and amore intensive treatment protocol with active exercise sessionsperformed 4 times per day starting 4 days after surgery. A treatmentplan may also include information pertaining to a medical procedure toperform on the patient, a treatment protocol for the patient using atreatment device, a diet regimen for the patient, a medication regimenfor the patient, a sleep regimen for the patient, additional regimens,or some combination thereof.

The terms telemedicine, telehealth, telemed, teletherapeutic,telemedicine, remote medicine, etc. may be used interchangeably herein.

The term “optimal treatment plan” may refer to optimizing a treatmentplan based on a certain parameter or factors or combinations of morethan one parameter or factor, such as, but not limited to, a measure ofbenefit which one or more exercise regimens provide to users, one ormore probabilities of users complying with one or more exerciseregimens, an amount, quality or other measure of sleep associated withthe user, information pertaining to a diet of the user, informationpertaining to an eating schedule of the user, information pertaining toan age of the user, information pertaining to a sex of the user,information pertaining to a gender of the user, an indication of amental state of the user, information pertaining to a genetic conditionof the user, information pertaining to a disease state of the user, anindication of an energy level of the user, information pertaining to amicrobiome from one or more locations on or in the user (e.g., skin,scalp, digestive tract, vascular system, etc.), or some combinationthereof.

As used herein, the term healthcare provider may include a medicalprofessional (e.g., such as a doctor, a nurse, a therapist, and thelike), an exercise professional (e.g., such as a coach, a trainer, anutritionist, and the like), or another professional sharing at leastone of medical and exercise attributes (e.g., such as an exercisephysiologist, a physical therapist, an occupational therapist, and thelike). As used herein, and without limiting the foregoing, a “healthcareprovider” may be a human being, a robot, a virtual assistant, a virtualassistant in virtual and/or augmented reality, or an artificiallyintelligent entity, such entity including a software program, integratedsoftware and hardware, or hardware alone.

Real-time may refer to less than or equal to 2 seconds. Near real-timemay refer to any interaction of a sufficiently short time to enable twoindividuals to engage in a dialogue via such user interface, and willpreferably but not determinatively be less than 10 seconds (or anysuitably proximate difference between two different times) but greaterthan 2 seconds.

Any of the systems and methods described in this disclosure may be usedin connection with rehabilitation. Rehabilitation may be directed atcardiac rehabilitation, rehabilitation from stroke, multiple sclerosis,Parkinson's disease, myasthenia gravis, Alzheimer's disease, any otherneurodegenative or neuromuscular disease, a brain injury, a spinal cordinjury, a spinal cord disease, a joint injury, a joint disease,post-surgical recovery, or the like. Rehabilitation can further involvemuscular contraction in order to improve blood flow and lymphatic flow,engage the brain and nervous system to control and affect a traumatizedarea to increase the speed of healing, reverse or reduce pain (includingarthralgias and myalgias), reverse or reduce stiffness, recover range ofmotion, encourage cardiovascular engagement to stimulate the release ofpain-blocking hormones or to encourage highly oxygenated blood flow toaid in an overall feeling of well-being. Rehabilitation may be providedfor individuals of average weight in reasonably good physical conditionhaving no substantial deformities, as well as for individuals moretypically in need of rehabilitation, such as those who are elderly,obese, subject to disease processes, injured and/or who have a severelylimited range of motion. Unless expressly stated otherwise, is to beunderstood that rehabilitation includes prehabilitation (also referredto as “pre-habilitation” or “prehab”). Prehabilitation may be used as apreventative procedure or as a pre-surgical or pre-treatment procedure.Prehabilitation may include any action performed by or on a patient (ordirected to be performed by or on a patient, including, withoutlimitation, remotely or distally through telemedicine) to, withoutlimitation, prevent or reduce a likelihood of injury (e.g., prior to theoccurrence of the injury); improve recovery time subsequent to surgery;improve strength subsequent to surgery; or any of the foregoing withrespect to any non-surgical clinical treatment plan to be undertaken forthe purpose of ameliorating or mitigating injury, dysfunction, or othernegative consequence of surgical or non-surgical treatment on anyexternal or internal part of a patient's body. For example, a mastectomymay require prehabilitation to strengthen muscles or muscle groupsaffected directly or indirectly by the mastectomy. As a furthernon-limiting example, the removal of an intestinal tumor, the repair ofa hernia, open-heart surgery or other procedures performed on internalorgans or structures, whether to repair those organs or structures, toexcise them or parts of them, to treat them, etc., can require cuttingthrough, dissecting and/or harming numerous muscles and muscle groups inor about, without limitation, the skull or face, the abdomen, the ribsand/or the thoracic cavity, as well as in or about all joints andappendages. Prehabilitation can improve a patient's speed of recovery,measure of quality of life, level of pain, etc. in all the foregoingprocedures. In one embodiment of prehabilitation, a pre-surgicalprocedure or a pre-non-surgical-treatment may include one or more setsof exercises for a patient to perform prior to such procedure ortreatment. Performance of the one or more sets of exercises may berequired in order to qualify for an elective surgery, such as a kneereplacement. The patient may prepare an area of his or her body for thesurgical procedure by performing the one or more sets of exercises,thereby strengthening muscle groups, improving existing muscle memory,reducing pain, reducing stiffness, establishing new muscle memory,enhancing mobility (i.e., improve range of motion), improving bloodflow, and/or the like.

The phrase, and all permutations of the phrase, “respective measure ofbenefit with which one or more exercise regimens may provide the user”(e.g., “measure of benefit,” “respective measures of benefit,” “measuresof benefit,” “measure of exercise regimen benefit,” “exercise regimenbenefit measurement,” etc.) may refer to one or more measures of benefitwith which one or more exercise regimens may provide the user.

DETAILED DESCRIPTION

The following discussion is directed to various embodiments of thepresent disclosure. Although one or more of these embodiments may bepreferred, the embodiments disclosed should not be interpreted, orotherwise used, as limiting the scope of the disclosure, including theclaims. In addition, one skilled in the art will understand that thefollowing description has broad application, and the discussion of anyembodiment is meant only to be exemplary of that embodiment, and notintended to intimate that the scope of the disclosure, including theclaims, is limited to that embodiment.

Determining optimal remote examination procedures to create an optimaltreatment plan for a patient having certain characteristics (e.g.,vital-sign or other measurements; performance; demographic;psychographic; geographic; diagnostic; measurement- or test-based;medically historic; behavioral historic; cognitive; etiologic;cohort-associative; differentially diagnostic; surgical, physicallytherapeutic, pharmacologic and other treatment(s) recommended; etc.) maybe a technically challenging problem. For example, a multitude ofinformation may be considered when determining a treatment plan, whichmay result in inefficiencies and inaccuracies in the treatment planselection process. In a rehabilitative setting, some of the multitude ofinformation considered may include characteristics of the patient suchas personal information, performance information, and measurementinformation. The personal information may include, e.g., demographic,psychographic or other information, such as an age, a weight, a gender,a height, a body mass index, a medical condition, a familial medicationhistory, an injury, a medical procedure, a medication prescribed, orsome combination thereof. The performance information may include, e.g.,an elapsed time of using a treatment device, an amount of force exertedon a portion of the treatment device, a range of motion achieved on thetreatment device, a movement speed of a portion of the treatment device,a duration of use of the treatment device, an indication of a pluralityof pain levels using the treatment device, or some combination thereof.The measurement information may include, e.g., a vital sign, arespiration rate, a heartrate, a temperature, a blood pressure, aglucose level or other biomarker, or some combination thereof. It may bedesirable to process and analyze the characteristics of a multitude ofpatients, the treatment plans performed for those patients, and theresults of the treatment plans for those patients.

Further, another technical problem may involve distally treating, via acomputing device during a telemedicine session, a patient from alocation different than a location at which the patient is located. Anadditional technical problem is controlling or enabling, from thedifferent location, the control of a treatment device used by thepatient at the patient's location. Oftentimes, when a patient undergoesrehabilitative surgery (e.g., knee surgery), a medical professional mayprescribe a treatment device to the patient to use to perform atreatment protocol at their residence or at any mobile location ortemporary domicile. A medical professional may refer to a doctor,physician assistant, nurse, chiropractor, dentist, physical therapist,acupuncturist, physical trainer, or the like. A medical professional mayrefer to any person with a credential, license, degree, or the like inthe field of medicine, physical therapy, rehabilitation, or the like.

When the healthcare provider is located in a location different from thepatient and the treatment device, it may be technically challenging forthe healthcare provider to monitor the patient's actual progress (asopposed to relying on the patient's word about their progress) in usingthe treatment device, modify the treatment plan according to thepatient's progress, adapt the treatment device to the personalcharacteristics of the patient as the patient performs the treatmentplan, and the like.

Further, in addition to the information described above, determiningoptimal examination procedures for a particular ailment (e.g., injury,disease, any applicable medical condition, etc.) may include physicallyexamining the injured body part of a patient. The healthcare provider,such as a physician or a physical therapist, may visually inspect theinjured body part (e.g., a knee joint). The inspection may includelooking for signs of inflammation or injury (e.g., swelling, redness,and warmth), deformity (e.g., symmetrical joints and abnormal contoursand/or appearance), or any other suitable observation. To determinelimitations of the injured body part, the healthcare provider mayobserve the injured body part as the patient attempts to perform normalactivity (e.g., bending and extending the knee and gauging anylimitations to the range of motion of the injured knee). The healthcareprovide may use one or more hands and/or fingers to touch the injuredbody part. By applying pressure to the injured body part, the healthcareprovider can obtain information pertaining to the extent of the injury.For example, the healthcare provider's fingers may palpate the injuredbody part to determine if there is point tenderness, warmth, weakness,strength, or to make any other suitable observation.

It may be desirable to compare characteristics of the injured body partwith characteristics of a corresponding non-injured body part todetermine what an optimal treatment plan for the patient may be suchthat the patient can obtain a desired result. Thus, the healthcareprovider may examine a corresponding non-injured body part of thepatient. For example, the healthcare provider's fingers may palpate anon-injured body part (e.g., a left knee) to determine a baseline of howthe patient's non-injured body part feels and functions. The healthcareprovider may use the results of the examination of the non-injured bodypart to determine the extent of the injury to the corresponding injuredbody part (e.g., a right knee). Additionally, injured body parts mayaffect other body parts (e.g., a knee injury may limit the use of theaffected leg, leading to atrophy of leg muscles). Thus, the healthcareprovider may also examine additional body parts of the patient forevidence of atrophy of or injury to surrounding ligaments, tendons,bones, and muscles, examples of muscles being such as quadriceps,hamstrings, or calf muscle groups of the leg with the knee injury. Thehealthcare provider may also obtain information as to a pain level ofthe patient before, during, and/or after the examination.

The healthcare provider can use the information obtained from theexamination (e.g., the results of the examination) to determine a propertreatment plan for the patient. If the healthcare provider cannotconduct a physical examination of the one or more body parts of thepatient, the healthcare provider may not be able to fully assess thepatient's injury and the treatment plan may not be optimal. Accordingly,embodiments of the present disclosure pertain to systems and methods forconducting a remote examination of a patient. The remote examinationsystem provides the healthcare provider with the ability to conduct aremote examination of the patient, not only by communicating with thepatient, but by virtually observing and/or feeling the patient's one ormore body parts.

In some embodiments, the systems and methods described herein may beconfigured for manipulation of a medical device. For example, thesystems and methods may be configured to use a medical device configuredto be manipulated by an individual while the individual is performing atreatment plan. The individual may include a user, patient, or other aperson using the treatment device to perform various exercises forprehabilitation, rehabilitation, stretch training, e.g., pliability,medical procedures, and the like. The systems and methods describedherein may be configured to use and/or provide a patient interfacecomprising an output device, wherein the output device is configured topresent telemedicine information associated with a telemedicine session.

In some embodiments, the systems and methods described herein may beconfigured for processing medical claims. For example, the systemincludes a processor configured to receive device-generated informationfrom a medical device. Using the device-generated information received,the processor is configured to determine device-based medical codinginformation. The processor is further configured to transmit thedevice-based medical coding information to a claim adjudication server.Any or all of the methods described may be implemented during atelemedicine session or at any other desired time.

In some embodiments, the medical claims may be processed, during atelemedicine or telehealth session, by a healthcare provider. Thehealthcare provider may select a particular treatment plan for thepatient to cause that treatment plan to be transmitted to the patientand/or to control, based on the treatment plan, the treatment device. Insome embodiments, to facilitate telehealth or telemedicine applications,including remote diagnoses, determination of treatment plans andrehabilitative and/or pharmacologic prescriptions, the artificialintelligence engine may receive data, instruct ructions, or the likeand/or operate distally from the patient and the treatment device.

In such cases, the recommended treatment plans and/or excluded treatmentplans may be presented simultaneously with a video of the patient inreal-time or near real-time during a telemedicine or telehealth sessionon a user interface of a computing device of a medical professional. Thevideo may also be accompanied by audio, text and other multimediainformation and/or other sensorial or perceptive (e.g., tactile,gustatory, haptic, pressure-sensing-based or electromagnetic (e.g.,neurostimulation), and without limitation, gesture recognition, gesturecontrol, touchless user interfaces (TUIs), kinetic user interfaces(KUIs), tangible user interfaces, wired gloves, depth-aware cameras,stereo cameras, and gesture-based controllers). Real-time may refer toless than or equal to 2 seconds. Near real-time may refer to anyinteraction of a sufficiently short time to enable two individuals toengage in a dialogue via such user interface, and will generally be lessthan 10 seconds (or any suitably proximate difference between twodifferent times) but greater than 2 seconds.

FIGS. 1-10 , discussed below, and the various embodiments used todescribe the principles of this disclosure are by way of illustrationonly and should not be construed in any way to limit the scope of thedisclosure.

FIG. 1 illustrates a component diagram of an illustrative medical system100 in accordance with aspects of this disclosure. The medical system100 may include a medical device 102. The medical device 102 may be atesting device, a diagnostic device, a therapeutic device, or any othersuitable medical device. “Medical device” as used in this context meansany hardware, software, mechanical, such as a treatment device (e.g.,medical device 102, treatment device 10, or the like), that may assistin a medical service, regardless of whether it is FDA (or othergovernmental regulatory body of any given country) approved, required tobe FDA (or other governmental regulatory body of any given country)approved or available commercially or to consumers without suchapproval. Non-limiting examples of medical devices include athermometer, an MRI machine, a CT-scan machine, a glucose meter, anapheresis machine, and a physical therapy machine, such as a physicaltherapy cycle. Non-limiting examples of places where the medical device102 may be located include a healthcare clinic, a physicalrehabilitation center, and a user's home to allow for telemedicinetreatment, rehabilitation, and/or testing. FIG. 2 illustrates an exampleof the medical device 102 where the medical device 102 is a physicaltherapy cycle.

As generally illustrated in FIG. 2 , the medical device 102 may comprisean electromechanical device, such as a physical therapy device. FIG. 2generally illustrates a perspective view of an example of a medicaldevice 102 according to certain aspects of this disclosure.Specifically, the medical device 102 illustrated is an electromechanicaldevice 202, such as an exercise and rehabilitation device (e.g., aphysical therapy device or the like). The electromechanical device 202is shown having pedal 210 on opposite sides that are adjustablypositionable relative to one another on respective radially-adjustablecouplings 208. The depicted electromechanical device 202 is configuredas a small and portable unit so that it is easily transported todifferent locations at which rehabilitation or treatment is to beprovided, such as at patients' homes, alternative care facilities, orthe like. The patient may sit in a chair proximate the electromechanicaldevice 202 to engage the electromechanical device 202 with the patient'sfeet, for example. The electromechanical device 202 includes a rotarydevice such as radially-adjustable couplings 208 or flywheel or the likerotatably mounted such as by a central hub to a frame or other support.The pedals 210 are configured for interacting with a patient to berehabilitated and may be configured for use with lower body extremitiessuch as the feet, legs, or upper body extremities, such as the hands,arms, and the like. For example, the pedal 210 may be a bicycle pedal ofthe type having a foot support rotatably mounted onto an axle withbearings. The axle may or may not have exposed end threads for engaginga mount on the radially-adjustable coupling 208 to locate the pedal onthe radially-adjustable coupling 208. The radially-adjustable coupling208 may include an actuator configured to radially adjust the locationof the pedal to various positions on the radially-adjustable coupling208.

Alternatively, the radially-adjustable coupling 208 may be configured tohave both pedals 210 on opposite sides of a single coupling 208. In someembodiments, as depicted, a pair of radially-adjustable couplings 208may be spaced apart from one another but interconnected to an electricmotor 206. In the depicted example, the computing device 112 may bemounted on the frame of the electromechanical device 202 and may bedetachable and held by the user while the user operates theelectromechanical device 202. The computing device 112 may present thepatient portal 212 and control the operation of the electric motor 206,as described herein.

In some embodiments, as described in U.S. Pat. No. 10,173,094 (U.S.application Ser. No. 15/700,293), which is incorporated by referenceherein in its entirety for all purposes, the medical device 102 may takethe form of a traditional exercise/rehabilitation device which is moreor less non-portable and remains in a fixed location, such as arehabilitation clinic or medical practice. The medical device 102 mayinclude a seat and is less portable than the medical device 102 shown inFIG. 2 . FIG. 2 is not intended to be limiting; the electromechanicaldevice 202 may include more or fewer components than those illustratedin FIG. 2 .

FIGS. 7-8 generally illustrate an embodiment of a treatment device, suchas a treatment device 10. More specifically, FIG. 7 generallyillustrates a treatment device 10 in the form of an electromechanicaldevice, such as a stationary cycling machine 14, which may be called astationary bike, for short. The stationary cycling machine 14 includes aset of pedals 12 each attached to a pedal arm 20 for rotation about anaxle 16. In some embodiments, and as generally illustrated in FIG. 8 ,the pedals 12 are movable on the pedal arm 20 in order to adjust a rangeof motion used by the patient in pedaling. For example, the pedals beinglocated inwardly toward the axle 16 corresponds to a smaller range ofmotion than when the pedals are located outwardly away from the axle 16.A pressure sensor 18 is attached to or embedded within one of the pedals12 for measuring an amount of force applied by the patient on the pedal102. The pressure sensor 18 may communicate wirelessly to the treatmentdevice 10 and/or to the patient interface 26. FIGS. 7-8 are not intendedto be limiting; the treatment device 10 may include more or fewercomponents than those illustrated in FIGS. 7-8 .

FIG. 9 generally illustrates a person (a patient) using the treatmentdevice 10 of FIG. 7 , and showing sensors and various data parametersconnected to a patient interface 26. The example patient interface 26 isa tablet computer or smartphone, or a phablet, such as an iPad, aniPhone, an Android device, or a Surface tablet, which is held manuallyby the patient. In some other embodiments, the patient interface 26 maybe embedded within or attached to the treatment device 10. FIG. 9generally illustrates the patient wearing the ambulation sensor 22 onhis wrist, with a note showing “STEPS TODAY 1355”, indicating that theambulation sensor 22 has recorded and transmitted that step count to thepatient interface 26. FIG. 9 also generally illustrates the patientwearing the goniometer 24 on his right knee, with a note showing “KNEEANGLE 72°”, indicating that the goniometer 24 is measuring andtransmitting that knee angle to the patient interface 26. FIG. 9generally illustrates a right side of one of the pedals 12 with apressure sensor 18 showing “FORCE 12.5 lbs.”, indicating that the rightpedal pressure sensor 18 is measuring and transmitting that forcemeasurement to the patient interface 26. FIG. 9 also generallyillustrates a left side of one of the pedals 12 with a pressure sensor18 showing “FORCE 27 lbs.”, indicating that the left pedal pressuresensor 18 is measuring and transmitting that force measurement to thepatient interface 26. FIG. 9 also generally illustrates other patientdata, such as an indicator of “SESSION TIME 0:04:13”, indicating thatthe patient has been using the treatment device 10 for 4 minutes and 13seconds. This session time may be determined by the patient interface 26based on information received from the treatment device 10. FIG. 9 alsogenerally illustrates an indicator showing “PAIN LEVEL 3”, Such a painlevel may be obtained from the patient in response to a solicitation,such as a question, presented upon the patient interface 26.

The medical device 102 may include an electromechanical device 104, suchas pedals of a physical therapy cycle, a goniometer configured to attachto a joint and measure joint angles, or any other suitableelectromechanical device 104. The electromechanical device 104 may beconfigured to transmit information, such as positioning information. Anon-limiting example of positioning information includes informationrelating to the location of pedals of the physical therapy cycle 200.The medical device 102 may include a sensor 106. The sensor 106 can beused for obtaining information to be used in generating a biometricsignature. A biometric signature, for the purpose of this disclosure, isa signature derived from certain biological characteristics of a user.The biometric signature can include information of a user, such asfingerprint information, retina information, voice information, heightinformation, weight information, vital sign information (e.g., bloodpressure, heart rate, etc.), response information to physical stimuli(e.g., change in heart rate while running on a treadmill), performanceinformation (rate of speed on the electromechanical device 104), or anyother suitable biological characteristic(s) of the user. The biometricsignature may include and/or be determined by a kinesiologicalsignature. A kinesiological signature, for the purpose of thisdisclosure, refers to a signature derived from human body movement, suchas information about a range of motion of or about a user's joint, e.g.,a knee, an elbow, a neck, a spine, or any other suitable joint,ligament, tendon, or muscle of a human. The sensor 106 may be atemperature sensor (such as a thermometer or thermocouple), a straingauge, a proximity sensor, an accelerometer, an inclinometer, aninfrared sensor, a pressure sensor, a light sensor, a smoke sensor, achemical sensor, any other suitable sensor, a fingerprint scanner, asound sensor, a microphone, or any combination thereof. The medicaldevice 102 may include, for obtaining information to be used ingenerating a biometric signature, a camera 108, such as a still imagecamera, a video camera, an infrared camera, an X-ray camera, any othersuitable camera, or any combination thereof. The medical device 102 mayinclude, for obtaining information to be used in generating a biometricsignature, an imaging device 110, such as an MRI imaging device, anX-ray imaging device, a thermal imaging device, any other suitableimaging device, or any combination thereof.

The medical device 102 may include, be coupled to, or be incommunication with a computing device 112. The computing device 112 mayinclude a processor 114. The processor 114 can include, for example,computers, intellectual property (IP) cores, application-specificintegrated circuits (ASICs), programmable logic arrays, opticalprocessors, programmable logic controllers, microcode, microcontrollers,servers, microprocessors, digital signal processors, any other suitablecircuit, or any combination thereof.

The computing device 112 may include a memory device 116 incommunication with the processor 114. The memory device 116 can includeany type of memory capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, aflash drive, a compact disc (CD), a digital video disc (DVD), solidstate drive (SSD), or any other suitable type of memory.

The computing device 112 may include an input device 118 incommunication with the processor 114. Examples of the input device 118include a keyboard, a keypad, a mouse, a microphone supported byspeech-to-text software, or any other suitable input device. The inputdevice 118 may be used by a medical system operator to inputinformation, such as user-identifying information, observational notes,or any other suitable information. An operator is to be understoodthroughout this disclosure to include both people and computer software,such as programs or artificial intelligence.

The computing device 112 may include an output device 120 incommunication with the processor 114. The output device 120 may be usedto provide information to the medical device operator or a user of themedical device 102. Examples of the output device 120 may include adisplay screen, a speaker, an alarm system, or any other suitable outputdevice, including haptic, tactile, olfactory, or gustatory ones, andwithout limitation, gesture recognition, gesture control, touchless userinterfaces (TUIs), kinetic user interfaces (KUIs), tangible userinterfaces, wired gloves, depth-aware cameras, stereo cameras, andgesture-based controllers. In some embodiments, such as where thecomputing device 112 includes a touchscreen, the input device 118 andthe output device 120 may be the same device.

For communicating with remote computers and servers, the computingdevice 112 may include a network adapter 122 in communication with theprocessor 114. The network adapter 122 may include wired or wirelessnetwork adapter devices or a wired network port.

Any time information is transmitted or communicated, the information maybe in EDI file format or any other suitable file format. In any of themethods or steps of the method, file format conversions may take place.By utilizing Internet of Things (IoT) gateways, data streams, ETLbucketing, EDI mastering, or any other suitable technique, data can bemapped, converted, or transformed into a carrier preferred state. As aresult of the volume of data being transmitted, the data securityrequirements, and the data consistency requirements, enterprise gradearchitecture may be utilized for reliable data transfer.

FIG. 1 is not intended to be limiting; the medical system 100 and thecomputing device 112 may include more or fewer components than thoseillustrated in FIG. 1 .

FIG. 3 illustrates a component diagram of an illustrative clinic serversystem 300 in accordance with aspects of this disclosure. The clinicserver system 300 may include a clinic server 302. The clinic serversystem 300 or clinic server 302 may be servers owned or controlled by amedical clinic (such as a doctor's office, testing site, or therapyclinic) or by a medical practice group (such as a testing company,outpatient procedure clinic, diagnostic company, or hospital). Theclinic server 302 may be proximate to the medical system 100. In otherembodiments, the clinic server 302 may be remote from the medical system100. For example, during telemedicine-based or telemedicine-mediatedtreatment, rehabilitation, or testing, the clinic server 302 may belocated at a healthcare clinic and the medical system 100 may be locatedat a patient's home. The clinic server 302 may be a rackmount server, arouter computer, a personal computer, a portable digital assistant, asmartphone, a laptop computer, a tablet computer, a netbook, a desktopcomputer, any other suitable computing device, or any combination of theabove. The clinic server 302 may be cloud-based or be a real-timesoftware platform, and it may include privacy (e.g., anonymization,pseudonymization, or other) software or protocols, and/or includesecurity software or protocols. The clinic server 302 may include acomputing device 304. The computing device 304 may include a processor306. The processor 306 can include, for example, computers, intellectualproperty (IP) cores, application-specific integrated circuits (ASICs),programmable logic arrays, optical processors, programmable logiccontrollers, microcode, microcontrollers, servers, microprocessors,digital signal processors, any other suitable circuit, or anycombination thereof.

The computing device 304 may include a memory device 308 incommunication with the processor 306. The memory device 308 can includeany type of memory capable of being accessed by a computer, such as readonly memory (ROM), random access memory (RAM), a hard disk drive, aflash drive, a compact disc (CD), a digital video disc (DVD), a solidstate drive (SSD), or any other suitable type of memory.

The computing device 304 may include an input device 310 incommunication with the processor 306. Examples of the input device 310include a keyboard, a keypad, a mouse, a microphone supported byspeech-to-text software, or any other suitable input device.

The computing device 304 may include an output device 312 incommunication with the processor 114. Examples of the output device 312include a display screen, a speaker, an alarm system, or any othersuitable output device, including haptic, tactile, olfactory, orgustatory ones, and without limitation, gesture recognition, gesturecontrol, touchless user interfaces (TUIs), kinetic user interfaces(KUIs), tangible user interfaces, wired gloves, depth-aware cameras,stereo cameras, and gesture-based controllers. In some embodiments, suchas where the computing device 304 includes a touchscreen, the inputdevice 310 and the output device 312 may be the same device.

The computing device 304 may include a network adapter 314 incommunication with the processor 306 for communicating with remotecomputers and/or servers. The network adapter 314 may include wired orwireless network adapter devices.

FIG. 3 is not intended to be limiting; the clinic server system 300, theclinic server 302, and the computing device 304 may include more orfewer components than those illustrated in FIG. 3 .

FIG. 4 illustrates a component diagram and method of an illustrativemedical claim processing system 400 and information flow according toaspects of this disclosure. The medical claim processing system 400 mayinclude the medical system 100. The medical claim processing system 400may include a clinic server 302.

The medical claim processing system 400 may include a patient notesdatabase 402. The patient notes database 402 may include informationinput by a clinic operator or information received from the clinicserver 302. For example, the clinic operator may enter informationobtained manually about a patient's height and weight and/or informationreceived from the patient about a condition from which the patient issuffering. The medical claim processing system 400 may include anelectronic medical records (EMR) database 404. The EMR database 404 mayinclude information input by a clinic operator and/or informationreceived from the clinic server 302 or the patient notes database 402.For example, the EMR database 404 may contain information received fromthe medical devices 102 or historical information obtained from patientnotes database 402, such as historical height and weight information.One or both of the patient notes database 402 and the EMR database 404may be located on the clinic server 302, on one or more remote servers,or on any other suitable system or server.

The medical claim processing system 400 may include a biller server 406.The biller server 406 may receive medical service information from themedical system 100; the clinic server 302; the patient notes database402; the EMR database 404; any suitable system, server, or database; orany combination thereof. The medical service information may includemedical coding information. By correlating the medical serviceinformation with an associated medical code, the biller server 406 maydetermine medical coding information. The biller server 406 maydetermine one or more responsible parties for payment of medical bills.Using the medical codes, the biller server 406 may generate an invoice.The biller server 406 may transmit the medical coding information andmedical service information to the responsible party or parties. Thebiller server 406 may be owned or controlled by a medical practice group(such as a testing company, an outpatient procedure clinic, a diagnosticcompany, or a hospital), a health insurance company, a governmentalentity, or any other organization (including third-party organizations)associated with medical billing procedures. The biller server 406 may bea rackmount server, a router computer, a personal computer, a portabledigital assistant, a smartphone, a laptop computer, a tablet computer, anetbook, a desktop computer, any other suitable computing device, or anycombination of the above. The biller server 406 may be cloud-based or bea real-time software platform, and it may include privacy (e.g.,anonymization, pseudonymization, or other) software or protocols, and/orinclude security software or protocols. The biller server 406 maycontain a computing device including any combination of the componentsof the computing device 304 as illustrated in FIG. 3 . The biller server406 may be proximate to or remote from the clinic server 302.

The medical claim processing system 400 may include a claim adjudicationserver 408. The claim adjudication server 408 may be owned or controlledby a health insurance company, governmental entity, or any otherorganization (including third-party organizations) associated withmedical billing procedures. The claim adjudication server 408 may be arackmount server, a router computer, a personal computer, a portabledigital assistant, a smartphone, a laptop computer, a tablet computer, anetbook, a desktop computer, any other suitable computing device, or anycombination of the above. The claim adjudication server 408 may becloud-based or be a real-time software platform, and it may includeprivacy (e.g., anonymization, pseudonymization, or other) software orprotocols, and/or include security software or protocols. The claimadjudication server 408 may contain a computing device including anycombination of the components of the computing device 304 as illustratedin FIG. 3 . The claim adjudication server 408 may be proximate to orremote from the biller server 406. The claim adjudication server 408 maybe configured to make or receive a determination about whether a claimshould be paid.

The medical claim processing system 400 may include a fraud, waste, andabuse (FWA) server 410. The FWA server 410 may be owned or controlled bya health insurance company, a governmental entity, or any otherorganization (including a third-party organization) associated withmedical billing procedures. The FWA server 410 may be a rackmountserver, a router computer, a personal computer, a portable digitalassistant, a smartphone, a laptop computer, a tablet computer, anetbook, a desktop computer, any other suitable computing device, or anycombination of the above. The FWA server 410 may be cloud-based or be areal-time software platform, and it may include privacy-enhancing,privacy-preserving, or privacy modifying software or protocols (e.g.,anonymization, pseudonymization, or other), and/or include securitysoftware or protocols. The FWA server 410 may contain a computing deviceincluding any combination of the components of the computing device 304as illustrated in FIG. 3 . The FWA server 410 may be proximate to orremote from the claim adjudication server 408. The FWA server 410 may beconfigured to make or receive a determination about whether a medicalclaim should be paid. The FWA server 410 may be configured to make orreceive a determination about whether a proposed payment for a medicalclaim is a result of fraud, waste, or abuse.

The medical claim processing system 400 may include a payment server412. The payment server 412 may be owned or controlled by a healthinsurance company, a governmental entity, or any other organization(including a third-party organization) associated with medical billingprocedures. The payment server 412 may be a rackmount server, a routercomputer, a personal computer, a portable digital assistant, asmartphone, a laptop computer, a tablet computer, a netbook, a desktopcomputer, any other suitable computing device, or any combination of theabove. The payment server 412 may be cloud-based or be a real-timesoftware platform, and it may include privacy-enhancing,privacy-preserving, or privacy modifying software or protocols (e.g.,anonymization, pseudonymization, or other), and/or include securitysoftware or protocols. The payment server 412 may contain a computingdevice including any combination of the components of the computingdevice 304. The payment server 412 may be proximate to or remote fromthe biller server 406 and/or the FWA server 410. The payment server 412may be configured to make or receive a determination about whether aclaim should be paid. The payment server 412 may be configured to makeor receive a determination about whether a proposed payment is, whollyor partially, a direct or indirect result of fraud, waste, or abuse. Thepayment server 412 may be configured to process or transmit a payment tothe service provider.

FIG. 4 is not intended to be limiting; the medical claim processingsystem 400 and any sub-components thereof may include more or fewercomponents, steps, and/or processes than those illustrated in FIG. 4 .Any of the components of the medical claim processing system 400 may bein direct or indirect communication with each other. Any or all of themethods described may be implemented during a telemedicine session or atany other desired time.

FIG. 5 illustrates a component diagram of an illustrative medical claimprocessing system 500 according to aspects of this disclosure. Themedical claim processing system 500 can include the medical system 100of FIG. 1 . The medical system 100 may be in communication with anetwork 502. The network 502 may be a public network (e.g., connected tothe Internet via wired (Ethernet) or wireless (Wi-Fi)), a privatenetwork (e.g., a local area network (LAN) or a wide area network (WAN)),a combination thereof, or any other suitable network.

The medical claim processing system 500 can include the clinic server302. The clinic server 302 may be in communication with the network 502.The clinic server 302 is shown as an example of servers that can be incommunication with the network 502. In addition to or in place of theclinic server 302, the medical claim processing system 500 can includethe biller server 406, the claim adjudication server 408, the FWA server410, the payment server 412, or any combination thereof.

The medical claim processing system 500 can include a cloud-basedlearning system 504. For example, the cloud-based learning system 504may be used to update or change a first biometric signature (i.e., apredicted biometric signature) of a user using historical device-basedsignature information relating to the user or other users, such as thosewith similar medical conditions, medical services provided,demographics, or any other suitable similarity. The cloud-based learningsystem 504 may be used to update or change an algorithm for generating asignature indicator. The signature indicator can include whether thefirst biometric signature (i.e., the predicted biometric signature)matches a second biometric signature (i.e., a device-based biometricsignature). Examples of signature indicators include flags andcomputer-coded variables. The cloud-based learning system 504 may be incommunication with the network 502. The cloud-based learning system 504may include one or more training servers 506 and form a distributedcomputing architecture. Each of the training servers 506 may include acomputing device, including any combination of one or more of thecomponents of the computing device 304 as illustrated in FIG. 3 , or anyother suitable components. The training servers 506 may be incommunication with one another via any suitable communication protocol.The training servers 506 may store profiles for users including, but notlimited to, patients, clinics, practice groups, and/or insurers. Theprofiles may include information such as historical device-generatedinformation, historical device-based medical coding information,historical reviewed medical coding information, historical electronicmedical records (EMRs), historical predicted biometric signatures,historical device-based biometric signatures, historical signaturecomparisons, historical signature indicators, historical emergencybiometric signatures, historical emergency comparisons, historicalemergency indicators, and any other suitable historical information.Other non-limiting examples of suitable historical information caninclude any information relating to a specific patient, a condition, ora population that was recorded at a time prior to the interactionpresently being billed as the medical claim.

In some aspects, the cloud-based learning system 504 may include atraining engine 508 capable of generating one or more machine learningmodels 510. The machine learning models 510 may be trained to generatealgorithms that aid in determining the device-based medical codinginformation, for example, by using the device generated information orgeneration of predicted biometric signatures, device-based biometricsignatures, signature indicators, emergency biometric signatures, and/oremergency indicators. For example, if the medical device 102 is an MRImachine, the machine learning models 510 may use the device-generatedinformation generated by the MRI machine (e.g., MRI images) to generateprogressively more accurate algorithms to determine which type ofmedical procedure (e.g., MM scan) was performed and which type ofmedical coding information (e.g., 73720, 73723, and 74183) to associatewith the medical procedure performed, predicted biometric signatures,and/or signature indicators. To generate the one or more machinelearning models 510, the training engine 508 may train the one or moremachine learning models 510. The training engine 508 may use a base dataset of historical device-generated information (e.g., generated from themedical device), historical device-based medical coding information,historical reviewed medical coding information, historical electronicmedical records (EMRs), historical predicted biometric signatures,historical device-based biometric signatures, historical signaturecomparisons, historical signature indicators, historical emergencybiometric signatures, historical emergency comparisons, historicalemergency indicators, and any other suitable historical information. Thetraining engine 508 may be in communication with the training servers506. The training engine 508 may be located on the training servers 506.

The training engine 508 may be a rackmount server, a router computer, apersonal computer, a portable digital assistant, a smartphone, a laptopcomputer, a tablet computer, a netbook, a desktop computer, an Internetof Things (IoT) node or sensor, any other suitable computing device, orany combination of the above. The training engine 508 may be cloud-basedor be a real-time software platform, and it may includeprivacy-enhancing, privacy-preserving, or privacy modifying software orprotocols (e.g., anonymization, pseudonymization, or other), and/orinclude security software or protocols. Using training data thatincludes training inputs and corresponding target outputs, the one ormore machine learning models 510 may refer to model artifacts created bythe training engine 508. The training engine 508 may find patterns inthe training data that map the training input to the target output andgenerate the machine learning models 510 that identify, store, or usethese patterns. Although depicted separately from the medical system100, the clinic server 302, the biller server 406, the claimadjudication server 408, the training engine 508, and the machinelearning models 510 may reside on the medical system 100. Alternatively,the clinic server 302, the biller server 406, the claim adjudicationserver 408, the training engine 508, and the machine learning models 510may reside on the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, anyother suitable computer device or server, or any combination thereof.

The machine learning models 510 may include one or more neural networks,such as an image classifier, a recurrent neural network, a convolutionalnetwork, a generative adversarial network, a fully connected neuralnetwork, any other suitable network, or combination thereof. In someembodiments, the machine learning models 510 may be composed of a singlelevel of linear or non-linear operations or may include multiple levelsof non-linear operations. For example, the machine learning models 510may include numerous layers and/or hidden layers that performcalculations (e.g., dot products) using various neural nodes.

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured toreceive device-generated information from a medical device. Thedevice-generated information may be information generated by the medicaldevice. The medical device may include the medical device 102. Themedical device 102 may include the medical system 100. Thedevice-generated information can include information obtained by theelectromechanical device 104, the sensor 106, the camera 108, theimaging device 110, any other portion of the medical device 102, anyseparate or remote electromechanical device, any separate or remotesensor, any separate remote camera, any separate or remote imagingdevice, any other suitable device, or any combination thereof. Thedevice-generated information may include vital sign information, such asheart rate, blood oxygen content, blood pressure, or any other suitablevital sign. The device-generated information may include images, such asMM images, X-ray images, video camera images, still camera images,infrared images, or any other suitable images. The device-generatedinformation may also include performance information (i.e., informationrelating to the physical performance of the user while the user operatesa medical device), such as a rate of pedaling of a physical therapycycle, a slope of a treadmill, a force applied to a strain-gauge, aweight lifted, a (simulated) distance traveled on a treadmill, or anyother suitable performance information. The device-generated informationmay include medical device use information, such as a location of themedical device 102, a healthcare provider associated with the medicaldevice 102, a practice group associated with the medical device 102, atime of day that the medical device 102 was used, a date that themedical device 102 was used, a duration that the medical device 102 wasused, or any other suitable medical device use information.

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured to usethe device-generated information to determine device-based medicalcoding information. Determining device-based medical coding informationcan include cross-referencing information about actions performed by orwith the medical device 102 contained within the device-generatedinformation with a reference list associating the actions performed byor with the medical device 102 with certain medical codes. The referencelist can be stored on the clinic server 302, as part of the cloud-basedlearning system 504, or on any other suitable server, database, orsystem. Determining device-based medical coding information can includeidentifying a portion of the device-generated information containingmedical coding information.

Any of the medical system 100, the computing device 112, the clinicserver 302, the biller server 406, the claim adjudication server 408,the FWA server 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof, may be configured to receive reviewed medicalcoding information. The reviewed medical coding information can includemedical coding information reviewed or entered by a clinic operator.Reviewed medical coding information can include information aboutpreviously performed medical processes, procedures, surgeries, or anyother suitable reviewed coding information. The reviewed medical codinginformation can be medical coding information that a clinic operator hasreviewed on a computing device or entered into a computing device. Forexample, a surgeon can review and revise, on a computing device, medicalcoding information about a surgery that the surgeon performed on apatient (user).

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured togenerate a predicted biometric signature (i.e., a first biometricsignature). The predicted biometric signature may include and/or bedetermined by a kinesiological signature. For example, the predictedbiometric signature can include a predicted movement such as a range ofmotion of a user's joint, such as a knee, an elbow, a neck, a spine, orany other suitable joint or muscle of a human. The predicted biometricsignature may be based at least in part on historical information. In anexample where a patient is using a physical therapy cycle 200, suchcycle preferably located at the patient's home or residence, as part oftelemedicine-enabled or -mediated rehabilitation therapy, then, usingpast camera images of the user taken by the device, the predictedbiometric signature can include an expected image of the user. Thepredicted biometric signature may be based at least in part on thereviewed medical coding information. For example, where a user hasundergone a specific back surgery, the predicted biometric signature mayinclude an Mill image of the user's upper back, such image showingevidence of that surgery. The predicted biometric signature may be basedat least in part on the device-based medical coding information. Forexample, if the device-based medical coding information indicates thatthe user has undergone an upper-back MM, the predicted biometricsignature may be based at least in part on how the image of the upperback is expected to appear based on other historical information, suchas past surgeries identified using the reviewed medical codinginformation. The predicted biometric signature may be based at least inpart on Electronic Medical Records (EMRs). For example, the predictedbiometric signature may be based at least in part on a height value anda weight value entered into the EMRs. The predicted biometric signaturemay be based at least in part on historical performance information(i.e., performance information generated in the past relating to aspecific user or other users). For example, the predicted biometricsignature may be based at least in part on a determination that apatient's performance on the physical therapy cycle 200 should be withina certain range of the patient's last performance on the physicaltherapy cycle 200. The determination may be modified using the amount oftime since the patient has last used the physical therapy cycle 200. Thepredicted biometric signature may be derived from any other suitableinformation, or any combination of any of the previous examples ofinformation from which the predicted biometric signature is derived.Further, if the predicted biometric signature includes a kinesiologicalsignature, the predicted biometric signature may be derived from anyother suitable information, or any combination of any of the previousexamples of information from which the predicted biometric signature isderived. For example, reviewed medical coding information relating to aknee surgery may be used to determine knee joint motion.

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured to, usingthe device-generated information, generate a device-based biometricsignature (i.e., a second biometric signature). The device-basedbiometric signature may be a kinesiological signature. For example, thedevice-based biometric signature can include the movement and jointrange of a user's knee. The device-based biometric signature may bebased at least in part on the device-based medical coding information.For example, where the device-based medical coding information suggeststhat the user has undergone an upper-back MM, the device-based biometricsignature may be based at least in part on the device-generatedinformation about the upper back. The device-based biometric signaturemay be based at least in part on the performance information. Forexample, the device-based biometric signature may be derived from a rateof pedaling of a physical therapy cycle 200, a slope of a treadmill, aforce applied to a strain-gauge, a weight lifted, a (simulated) distancetraveled on a treadmill, or any other suitable performance information.The device-based biometric signature may be derived from images includedin the device-generated information, such as MRI images, X-ray images,video camera images, still camera images, infrared images, or any othersuitable images. The device-based biometric signature may be derivedfrom any other suitable information, or any combination of any of theprevious examples of information upon with the device-based biometricsignature is based. Further, if the device-based biometric signatureincludes a kinesiological signature, the device-based biometricsignature may be derived from any other suitable information, or anycombination of any of the previous examples of information upon with thedevice-based biometric signature is based. For example, camera imagesmay be used to determine knee joint motion as a kinesiological signatureembodiment of the device-based biometric signature.

Any of the medical system 100, the computing device 112 of the medicalsystem 100, clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured to usethe predicted biometric signature and the device-based biometricsignature to generate a signature comparison. The signature comparisoncan include differences in terms of degrees between the predictedbiometric signature and the device-based biometric signature. Forexample, if the predicted biometric signature includes heightinformation for a user with a value of 5 feet 4 inches and thedevice-based biometric signature includes height information for a userwith a value of 5 feet 5 inches, the degree of difference between thepredicted biometric signature and the device-based biometric signaturemay be indicated to be below a FWA threshold value. However, if thepredicted biometric signature includes height information for a userwith a value of 5 feet 4 inches and the device-based biometric signatureincludes height information for a user with a value of 5 feet 9 inchestall, the degree of difference between the predicted biometric signatureand the device-based biometric signature may be noted to be above theFWA threshold value.

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured to usethe signature comparison to generate a signature indicator. To indicatean incorrect user, the signature indicator can include flagging when thesignature comparison is outside an acceptable user threshold. Forexample, if the predicted biometric signature includes heightinformation for a user with a height value of 5 feet 4 inches tall andthe device-based biometric signature includes height information for auser with a value of 5 feet 9 inches tall, a signature indicator may begenerated. The signature indicator may indicate that the differencebetween the predicted biometric signature and the device-based biometricsignature is above the FWA threshold value. This difference may be theresult of an incorrect user using the medical device. Another exampleincludes generating a signature indicator in response to differences inbetween the predicted biometric signature and the device-based biometricsignature, as derived from the performance metric information and thevital sign information, such that the processor 114 determines that thedifferences are above a FWA threshold. In response to thisdetermination, the processor 114 generates the signature indicator. Inthis example, a post-knee surgery user walked a mile in 45 minutes on atreadmill with an average heartrate of 190 beats per minute (bpm) (i.e.,the user struggled to walk a mile) and the same user later walked 5miles on the treadmill in 45 minutes with a heartrate of 130 bpm (i.e.,the user did not struggle to walk more than a mile in the same time).Another example includes a camera image displaying different images ofusers for the same billing user, as determined by using facialrecognition software. Another example includes a user with a low rangeof movement in his knee joint on a first day and the same user with ahigh range of movement in his knee joint on a consecutive day (i.e., akinesiological signature above the FWA threshold). The signatureindicator can include flagging if the differences are determined to bethe result of any errors or inconsistencies in the EMRs or reviewedmedical coding information. For example, if the predicted biometricsignature is based on a certain type of surgery, and the device-basedbiometric signature is not consistent with such surgery (i.e.,consistent with a less-intense surgery—perhaps one not requiring asintense or expensive a physical therapy regimen), a signature indicatormay be generated. The signature indicator may be transmitted to anoperator to indicate that there is an error or an inconsistency in theEMRs or reviewed medical coding information.

Any of the medical system 100, the computing device 112, the clinicserver 302, the biller server 406, the claim adjudication server 408,the FWA server 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof may be configured to transmit the signatureindicator. For example, any of the medical system 100, the computingdevice 112 of the medical system 100, the clinic server 302, the billerserver 406, the claim adjudication server 408, the FWA server 410, thepayment server 412, the training server 506, the training engine 508,any other suitable computing device, or any combination thereof maytransmit the signature indicator (e.g., a flag) to the medical system100, the computing device 112 of the medical system 100, clinic server302, the biller server 406, the claim adjudication server 408, the FWAserver 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof.

The signature indicator may be used by the receiving system or theserver. In one exemplary embodiment, at the medical system 100, thesignature indicator can be used to validate information and/or to set aflag to inform an operator of the medical system 100 or medical device102 that there is a biometric signature mismatch and, for example, thewrong therapy may have been prescribed to a patient. In anotherexemplary embodiment, the clinic server 302 can use the signatureindicator to validate information and/or to determine whether totransmit a message to an operator or administrator. The message mayinclude information indicating a biometric signature mismatch and/orinformation improperly entered into the EMR database 404. In anotherexemplary embodiment, the biller server 406 may use the signatureindicator to validate information received or sent and/or to not sendthe medical coding information to the claim adjudication server 408until the biometric signature is matched. In another exemplaryembodiment, the claim adjudication server 408 may use the may use thesignature indicator to (1) validate information received; (2) determinethat a flag should be added to the medical coding information prior totransmitting the medical coding information to the FWA server 410 and/orthe payment server 412; or (3) receive additional information from theFWA server 410. In another exemplary embodiment, the FWA server 410 canuse the signature indicator to (1) validate information received, (2)determine whether to transmit a message, and/or (3) make a determinationof whether to flag the medical coding information as fraudulent andtransmit a message to initiate a FWA investigation. In another exemplaryembodiment, the payment server 412 can use the signature indicator tovalidate information received and/or to determine whether to pay themedical service provider. In another exemplary embodiment, the trainingserver 506 and/or the training engine 508 can use the signatureindicator for further machine learning activities (i.e., by increasingthe size of the dataset every time a signature indicator is generated).

Any of the medical system 100, the computing device 112 of the medicalsystem 100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, any other suitablecomputing device, or any combination thereof may be configured togenerate an emergency biometric signature for use in detecting andresponding to an emergency event. When a user is undergoingtelemedicine-enabled or -mediated rehabilitation therapy without directsupervision by a trained medical professional, automatically (including,without limitation, through means of artificial intelligence and/ormachine learning) recognizing and responding to emergency events may bedesirable in the event that an emergency situation occurs. The emergencybiometric signature can be derived from the predicted biometricsignature. The emergency biometric signature may include vital signinformation (a user's heart rate or blood pressure being too high or toolow), imagery (a user's face turning purple), or any other suitableinformation. In an example where a patient is using a physical therapycycle 200 located at the patient's home or residence to undergotelemedicine-enabled or -mediated rehabilitation therapy, the emergencybiometric signature can include a value of a heart-rate of a user thatis above an emergency threshold value. The emergency threshold may bederived from the predicted biometric signature. The value above theemergency threshold value may indicate an emergency condition. Theemergency biometric signature can include a kinesiological signature,such as where the emergency biometric signature includes a knee jointhaving a range of greater than 180°. Non-limiting examples of emergencyconditions include broken bones, heart attacks, and blood loss.

Any of the medical system 100, the computing device 112, the clinicserver 302, the biller server 406, the claim adjudication server 408,the FWA server 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof may be configured to use the device-based biometricsignature and/or an emergency biometric signature to generate anemergency comparison. The emergency comparison can be derived from vitalsign information, imagery, or any other suitable information. Forexample, a device-based biometric signature including a heart rate valueof 0 bpm can be compared to an emergency biometric signature includingan emergency range of heart rate values of 0-40 bpm. In this example,the emergency comparison indicates that the device-based biometricsignature heart rate is within the emergency range. As another example,a device-based biometric signature including a user's face being a shadeof purple can be compared to an emergency biometric signature includingan emergency range of shades of the user's face. In this example, theemergency comparison indicates that the shade of the user's face iswithin the emergency range. As yet another example, a device-basedbiometric signature in which the range of motion of the user's joint hasextended to 270° can be compared to an emergency biometric signature inwhich an emergency range of knee joint extension includes values greaterthan 180°. In this example, the emergency comparison indicates that theknee joint range is in the emergency range.

Any of the medical system 100, the computing device 112, the clinicserver 302, the biller server 406, the claim adjudication server 408,the FWA server 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof may be configured to use the emergency comparison togenerate an emergency indicator. The emergency indicator can includewhether an emergency biometric signature matches a device-basedbiometric signature. Examples of the emergency indicators include flagsand saved variables. For example, the emergency indicator can begenerated when the comparison indicates a similarity or overlap betweenthe device-based biometric signature and the emergency biometricsignature. For example, the emergency indicator can be derived from theemergency comparison if the emergency comparison indicates that the kneejoint range is in the emergency range.

Any of the medical system 100, the computing device 112, the clinicserver 302, the biller server 406, the claim adjudication server 408,the FWA server 410, the payment server 412, the training server 506, thetraining engine 508, any other suitable computing device, or anycombination thereof may be configured to transmit the emergencyindicator. For example, any of the medical system 100, the computingdevice 112 of the medical system 100, the clinic server 302, the billerserver 406, the claim adjudication server 408, the FWA server 410, thepayment server 412, the training server 506, the training engine 508,any other suitable computing device, or any combination thereof maytransmit the emergency indicator to the medical system 100, thecomputing device 112 of the medical system 100, the clinic server 302,the biller server 406, the claim adjudication server 408, the FWA server410, the payment server 412, the training server 506, the trainingengine 508, an emergency services system or computer, any other suitablecomputing device, or any combination thereof. Further, the biometricinformation may also be transmitted to provide emergency or clinicservices with information about the nature of the emergency. Further,the medical system 100, the computing device 112 of the medical system100, the clinic server 302, the biller server 406, the claimadjudication server 408, the FWA server 410, the payment server 412, thetraining server 506, the training engine 508, an emergency servicessystem or computer, any other suitable computing device, or anycombination thereof can activate an output device 120, such as an alarmsystem. The alarm system can include a speaker, a siren, a system thatcontacts emergency services (e.g., to summon an ambulance), a flashinglight, any other suitable alarm component, or any combination thereof.

FIG. 5 is not intended to be limiting; the medical claim processingsystem 500, the medical system 100, computing device 112, the clinicserver 302, the clinic server 302, the computing device 304, thecloud-based learning system 504, and any sub-components thereof mayinclude more or fewer components than those illustrated in FIG. 5 .

FIGS. 6A and 6B illustrate a computer-implemented method 600 forprocessing medical claims. The method 600 may be performed on themedical system 100, the computing device 112, the clinic server 302, thebiller server 406, the claim adjudication server 408, the FWA server410, the payment server 412, the training server 506, the trainingengine 508, any other suitable computing device, or any combinationthereof. The method 600 may be implemented on a processor, such as theprocessor 306, configured to perform the steps of the method 600. Themethod 600 may be implemented on a system, such as the medical system100 or the clinic server system 300, that includes a processor, such asthe processor 306, and a memory device, such as the memory device 308.The method 600 may be implemented on the clinic server system 300. Themethod 600 may include operations that are implemented in instructionsstored in a memory device, such as the memory device 308, and executedby a processor, such as the processor 306, of a computing device, suchas the computing device 304. The steps of the method 600 may be storedin a non-transient computer-readable storage medium.

At step 602, the method 600 can include receiving device-generatedinformation from a medical device, such as the medical device 102. Forexample, the clinic server 302 can receive (1) knee angle informationfrom a goniometer attached to a knee of a user of the physical therapycycle 200; and (2) pedal speed information and force information fromthe physical therapy cycle 200. After the clinic server 302 receives thedevice-generated information from the medical device 102, the clinicserver 302 can proceed to step 604 or to step 610. Alternatively, theclinic server 302 can proceed to steps 604 and 610.

At step 604, the method 600 can include using the device-generatedinformation to determine device-based medical coding information. Forexample, the clinic server 302 can use the pedal speed informationand/or force information from the physical therapy cycle to determinethat the user is undergoing a one-hour therapy session. The clinicserver 302 can access the EMRs associated with the user to determinewhich information is relevant to the therapy session (e.g., that theuser has a prior right knee injury). The clinic server 302 can determinemedical coding information associated with one-hour therapy sessions fora right knee injury. After the clinic server 302 determines thedevice-based medical information, the clinic server 302 can proceed tostep 606.

At step 606, the method 600 can include receiving reviewed medicalcoding information. For example, the clinic server 302 can receiveinformation input by a doctor that the user has an injury to the user'sleft knee. After the clinic server 302 receives the reviewed medicalcoding information, the clinic server 302 can proceed to step 608.

At step 608, the method 600 can include receiving electronic medicalrecords (EMRs) for a user of a medical device 102. For example, theclinic server 302 can receive information from the EMRs. The informationcan indicate that the user has an injury to the user's left knee. Afterthe clinic server 302 receives the EMRs, the clinic server 302 canproceed to step 610.

At step 610, the method 600 can include generating a first biometricsignature (i.e., a predicted biometric signature). The clinic server 302can generate the first biometric signature. The first biometricsignature may be a kinesiological signature of a user. For example, theclinic server 302 can use the injury and the past performance of theuser to generate a first biometric signature, which may include a firstkinesiological signature (i.e., an emergency kinesiological signature)having a predicted left knee joint range of motion between approximately130°-140° and a predicted right knee joint range of motion betweenapproximately 165-170°. After the clinic server 302 generates the firstbiometric signature, the clinic server 302 can proceed to step 612.

At step 612, the method 600 can include generating, using thedevice-generated information, a second biometric signature (i.e., adevice-based biometric signature). The second biometric signature may bea kinesiological signature. For example, the clinic server 302 cangenerate, using the measurements from the goniometer, a second biometricsignature including a second kinesiological signature (i.e., adevice-based kinesiological signature) having a left knee joint range ofmotion of approximately 170° and a right knee joint range of motion ofapproximately 135°. After the clinic server 302 generates the secondbiometric signature, the clinic server 302 can proceed to step 614.

At step 614, the method 600 can include comparing the first and secondbiometric signatures. For example, the clinic server 302 can compare thepredicted left knee joint range of motion (i.e., the first biometricsignature having a predicted a range of motion of approximately)130°-140° and the measured a left knee joint range of motion (i.e., thesecond biometric signature with a measured range of motion ofapproximately 170°). After the clinic server 302 generates compares thefirst and second biometric signatures, the clinic server 302 can proceedto step 616.

At step 616, the method 600 can include generating, using the firstbiometric signature and the second biometric signature, a signaturecomparison. For example, the clinic server 302 can generate a signaturecomparison showing that the user's left knee joint range of motion isoutside of the expected range of motion for the user's left knee joint(e.g., approximately 30° above the expected maximum range of motion).The clinic server 302 can generate one or more signature comparisons.For example, the clinic server 302 can generate a second signalcomparison that the user's right knee joint range of motion is outsideof the expected range of motion for the user's right knee joint (e.g.,approximately 30° below the expected minimum range of motion). After theclinic server 302 generates the signature comparison, the clinic server302 can proceed to step 618.

At step 618, the method 600 can include generating, using the signaturecomparison, a signature indicator (e.g., a variable or flag thatindicates whether the differences between the first and second biometricsignatures exceed a FWA threshold value). The signature indicator caninclude flagging if the differences are determined to be the result ofan incorrect user. For example, the clinic server 302 can use the leftknee joint range of motion being outside of an expected range of motionthreshold to generate a signature indicator flagging that the user maybe an incorrect user, that there may be an error in the medical records,that the goniometer measurements may have been incorrect (e.g., anotheruser's medical records) resulting from an operator error, or that anyother suitable error has occurred. After the clinic server 302 generatesthe signature indicator, the clinic server 302 can proceed to step 620.

At step 620, the method 600 can include transmitting the signatureindicator. For example, the clinic server 302 may transmit the signatureindicator to the biller server 406. After the clinic server 302transmits the signature indicator, the clinic server 302 can end themethod or proceed to step 622.

At step 622, the method 600 can include generating an emergencybiometric signature including information indicative of an emergencyevent (e.g., a heart attack, broken bone, blood loss, etc.). Forexample, the clinic server 302 can generate an emergency biometricsignature having a knee joint range of motion in excess of 185°. Afterthe clinic server 302 generates the emergency biometric signature, theclinic server 302 can proceed to step 624.

At step 624, the method 600 can include using the second biometricsignature and the emergency biometric signature to generate an emergencycomparison. For example, if the emergency biometric signature isgenerated when a knee joint range of motion of a user operating thephysical therapy cycle 200 is greater than an emergency threshold of185° and the second biometric signature determines that a knee jointrange of motion of a user operating the physical therapy cycle 200 isapproximately 270°, the user has exceeded the emergency threshold andthe clinic server 302 can generate the emergency comparison. After theclinic server 302 generates the emergency comparison, the clinic server302 can proceed to step 626.

At step 626, the method 600 can include, using the emergency comparisonto generate an emergency indicator. For example, using the secondbiometric signature having a knee joint range of motion exceeding theemergency threshold of the emergency biometric signature (e.g., theuser's range of motion is 85° greater than the emergency biometricsignature), the clinic server 302 can determine that there is anemergency condition. After the clinic server 302 generates the emergencyindicator, the clinic server 302 can proceed to step 628.

At step 628, the method 600 can include transmitting the emergencyindicator. For example, in response to the generation of the emergencyindicator, the clinic server 302 can transmit the emergency indicator toan on-site registered nurse. The emergency indicator may includeinformation, device-generated information, EMRs, the emergencycomparison, any other suitable information, or any combination thereof.

FIGS. 6A and 6B are not intended to be limiting; the method 600 caninclude more or fewer steps and/or processes than those illustrated inFIG. 6 . Further, the order of the steps of the method 600 is notintended to be limiting; the steps can be arranged in any suitableorder. Any or all of the steps of method 600 may be implemented during atelemedicine session or at any other desired time.

FIG. 10 shows an example computer system 800 which can perform any oneor more of the methods described herein, in accordance with one or moreaspects of the present disclosure. In one example, computer system 800may include a computing device and correspond to an assistanceinterface, a reporting interface, a supervisory interface, a clinicianinterface, a server (including an AI engine), a patient interface, anambulatory sensor, a goniometer, a treatment device 10, a medical device102, a pressure sensor, or any suitable component. The computer system800 may be capable of executing instructions implementing the one ormore machine learning models of the artificial intelligence engine. Thecomputer system may be connected (e.g., networked) to other computersystems in a LAN, an intranet, an extranet, or the Internet, includingvia the cloud or a peer-to-peer network. The computer system may operatein the capacity of a server in a client-server network environment. Thecomputer system may be a personal computer (PC), a tablet computer, awearable (e.g., wristband), a set-top box (STB), a personal DigitalAssistant (PDA), a mobile phone, a camera, a video camera, an Internetof Things (IoT) device, or any device capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that device. Further, while only a single computer system isillustrated, the term “computer” shall also be taken to include anycollection of computers that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of the methodsdiscussed herein.

The computer system 800 includes a processing device 802, a main memory804 (e.g., read-only memory (ROM), flash memory, solid state drives(SSDs), dynamic random access memory (DRAM) such as synchronous DRAM(SDRAM)), a static memory 806 (e.g., flash memory, solid state drives(SSDs), static random access memory (SRAM)), and a data storage device808, which communicate with each other via a bus 810.

Processing device 802 represents one or more general-purpose processingdevices such as a microprocessor, central processing unit, or the like.More particularly, the processing device 802 may be a complexinstruction set computing (CISC) microprocessor, reduced instruction setcomputing (RISC) microprocessor, very long instruction word (VLIW)microprocessor, or a processor implementing other instruction sets orprocessors implementing a combination of instruction sets. Theprocessing device 802 may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), asystem on a chip, a field programmable gate array (FPGA), a digitalsignal processor (DSP), network processor, or the like. The processingdevice 802 is configured to execute instructions for performing any ofthe operations and steps discussed herein.

The computer system 800 may further include a network interface device812. The computer system 800 also may include a video display 814 (e.g.,a liquid crystal display (LCD), a light-emitting diode (LED), an organiclight-emitting diode (OLED), a quantum LED, a cathode ray tube (CRT), ashadow mask CRT, an aperture grille CRT, a monochrome CRT), one or moreinput devices 816 (e.g., a keyboard and/or a mouse or a gaming-likecontrol), and one or more speakers 818 (e.g., a speaker). In oneillustrative example, the video display 814 and the input device(s) 816may be combined into a single component or device (e.g., an LCD touchscreen).

The data storage device 816 may include a computer-readable medium 820on which the instructions 822 embodying any one or more of the methods,operations, or functions described herein is stored. The instructions822 may also reside, completely or at least partially, within the mainmemory 804 and/or within the processing device 802 during executionthereof by the computer system 800. As such, the main memory 804 and theprocessing device 802 also constitute computer-readable media. Theinstructions 822 may further be transmitted or received over a networkvia the network interface device 812.

While the computer-readable storage medium 820 is shown in theillustrative examples to be a single medium, the term “computer-readablestorage medium” should be taken to include a single medium or multiplemedia (e.g., a centralized or distributed database, and/or associatedcaches and servers) that store the one or more sets of instructions. Theterm “computer-readable storage medium” shall also be taken to includeany medium that is capable of storing, encoding or carrying a set ofinstructions for execution by the machine and that cause the machine toperform any one or more of the methodologies of the present disclosure.The term “computer-readable storage medium” shall accordingly be takento include, but not be limited to, solid-state memories, optical media,and magnetic media.

FIG. 10 is not intended to be limiting; the system 800 may include moreor fewer components than those illustrated in FIG. 10 .

The term “computer-readable storage medium” should be taken to include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore sets of instructions. The term “computer-readable storage medium”shall also be taken to include any medium capable of storing, encodingor carrying a set of instructions for execution by the machine andcausing the machine to perform any one or more of the methodologies ofthe present disclosure. The term “computer-readable storage medium”shall accordingly be taken to include, but not be limited to,solid-state memories, optical media, and magnetic media.

Any of the systems and methods described in this disclosure may be usedin connection with rehabilitation. Unless expressly stated otherwise, isto be understood that rehabilitation includes prehabilitation (alsoreferred to as “pre-habilitation” or “prehab”). Prehabilitation may beused as a preventative procedure or as a pre-surgical or pre-treatmentprocedure. Prehabilitation may include any action performed by or on apatient (or directed to be performed by or on a patient, including,without limitation, remotely or distally through telemedicine) to,without limitation, prevent or reduce a likelihood of injury (e.g.,prior to the occurrence of the injury); improve recovery time subsequentto surgery; improve strength subsequent to surgery; or any of theforegoing with respect to any non-surgical clinical treatment plan to beundertaken for the purpose of ameliorating or mitigating injury,dysfunction, or other negative consequence of surgical or non-surgicaltreatment on any external or internal part of a patient's body. Forexample, a mastectomy may require prehabilitation to strengthen musclesor muscle groups affected directly or indirectly by the mastectomy. As afurther non-limiting example, the removal of an intestinal tumor, therepair of a hernia, open-heart surgery or other procedures performed oninternal organs or structures, whether to repair those organs orstructures, to excise them or parts of them, to treat them, etc., canrequire cutting through and harming numerous muscles and muscle groupsin or about, without limitation, the abdomen, the ribs and/or thethoracic cavity. Prehabilitation can improve a patient's speed ofrecovery, measure of quality of life, level of pain, etc. in all theforegoing procedures. In one embodiment of prehabilitation, apre-surgical procedure or a pre-non-surgical-treatment may include oneor more sets of exercises for a patient to perform prior to suchprocedure or treatment. The patient may prepare an area of his or herbody for the surgical procedure by performing the one or more sets ofexercises, thereby strengthening muscle groups, improving existingand/or establishing new muscle memory, enhancing mobility, improvingblood flow, and/or the like.

In some embodiments, the systems and methods described herein may useartificial intelligence and/or machine learning to generate aprehabilitation treatment plan for a user. Additionally, oralternatively, the systems and methods described herein may useartificial intelligence and/or machine learning to recommend an optimalexercise machine configuration for a user. For example, a data model maybe trained on historical data such that the data model may be providedwith input data relating to the user and may generate output dataindicative of a recommended exercise machine configuration for aspecific user. Additionally, or alternatively, the systems and methodsdescribed herein may use machine learning and/or artificial intelligenceto generate other types of recommendations relating to prehabilitation,such as recommended reading material to educate the patient, arecommended health professional specialist to contact, and/or the like.

Consistent with the above disclosure, the examples of systems and methodenumerated in the following clauses are specifically contemplated andare intended as a non-limiting set of examples.

Clause 1. A computer-implemented system for processing medical claims,comprising:

a medical device configured to be manipulated by a user while the userperforms a treatment plan;

a patient interface associated with the medical device, the patientinterface comprising an output configured to present telemedicineinformation associated with a telemedicine session; and

a processor configured to:

-   -   during the telemedicine session, receive device-generated        information from the medical device;    -   generate a first biometric signature;    -   using the device-generated information, generate a second        biometric signature;    -   using the first and second biometric signatures, generate a        signature comparison;    -   using the signature comparison, generate a signature indicator;        and    -   transmit the signature indicator.

Clause 2. The computer-implemented system of any clause herein, wherein:

the device-generated information is generated by the medical device;

using the device-generated information, the processor is furtherconfigured to determine device-based medical coding information; and

generating the second biometric signature uses the device-based medicalcoding information.

Clause 3. The computer-implemented system of any clause herein, whereinthe processor is further configured to receive reviewed medical codinginformation; and

wherein generating the first biometric signature uses the reviewedmedical coding information.

Clause 4. The computer-implemented system of any clause herein, whereinthe processor is further configured to receive electronic medicalrecords pertaining to the user of the medical device; and

wherein generating the first biometric signature uses the electronicmedical records.

Clause 5. The computer-implemented system of any clause herein, whereinthe processor is further configured to:

using the second biometric signature and an emergency biometricsignature, generate an emergency comparison;

using the emergency comparison, generate an emergency indicator; and

transmit the emergency indicator.

Clause 6. A system for processing medical claims, comprising:

a processor configured to:

-   -   receive device-generated information from a medical device;    -   generate a first biometric signature;    -   using the device-generated information, generate a second        biometric signature;    -   using the first biometric signature and the second biometric        signature, compare the signatures;    -   using the first and second biometric signatures, generate a        signature comparison;    -   using the signature comparison, generate a signature indicator;        and    -   transmit the signature indicator.

Clause 7. The system of any clause herein, wherein the device-generatedinformation is generated by the medical device.

Clause 8. The system of any clause herein, wherein, using thedevice-generated information, the processor is further configured todetermine device-based medical coding information; and

wherein generating the second biometric signature uses the device-basedmedical coding information.

Clause 9. The system of any clause herein, wherein the processor isfurther configured to receive reviewed medical coding information; and

wherein generating the first biometric signature uses the reviewedmedical coding information.

Clause 10. The system of any clause herein, wherein the processor isfurther configured to receive electronic medical records pertaining to auser of the medical device; and

wherein generating the first biometric signature uses the electronicmedical records.

Clause 11. The system of any clause herein, wherein the processor isfurther configured to:

using the second biometric signature and an emergency biometricsignature, generate an emergency comparison;

using the emergency comparison, generate an emergency indicator; and

transmit the emergency indicator.

Clause 12. The system of any clause herein, wherein the processor isfurther configured to generate the emergency biometric signature.

Clause 13. The system of any clause herein, wherein the device-generatedinformation includes at least one of vital sign information, images, andmedical device use information.

Clause 14. The system of any clause herein, wherein the device-generatedinformation includes performance information; and

wherein generating the second biometric signature uses the performanceinformation.

Clause 15. The system of any clause herein, wherein generating the firstbiometric signature uses historical performance information.

Clause 16. The system of any clause herein, wherein the first biometricsignature includes a first kinesiological signature; and

wherein the second biometric signature includes a second kinesiologicalsignature.

Clause 17. The system of any clause herein, further comprising a memorydevice operatively coupled to the processor, wherein the memory devicestores instructions, and wherein the processor is configured to executethe instructions.

Clause 18. A method for processing medical claims, comprising:

receiving device-generated information from a medical device;

generating a first biometric signature;

using the device-generated information, generating a second biometricsignature;

using the first biometric signature and the second biometric signature,generating a signature comparison;

using the signature comparison, generating a signature indicator; and

transmitting the signature indicator.

Clause 19. The method of any clause herein, wherein the device-generatedinformation is generated by the medical device.

Clause 20. The method of any clause herein, further comprising using thedevice-generated information to determine device-based medical codinginformation;

wherein generating the second biometric signature uses the device-basedmedical coding information.

Clause 21. The method of any clause herein, further comprising receivingreviewed medical coding information; wherein generating the firstbiometric signature uses the reviewed medical coding information.

Clause 22. The method of any clause herein, further comprising receivingelectronic medical records pertaining to a user of the medical device;wherein generating the first biometric signature uses the electronicmedical records.

Clause 23. The method of any clause herein, further comprising:

using the second biometric signature and an emergency biometricsignature to generate an emergency comparison;

using the emergency comparison to generate an emergency indicator; and

transmitting the emergency indicator.

Clause 24. The method of any clause herein, further comprisinggenerating the emergency biometric signature.

Clause 25. The method of any clause herein, wherein the device-generatedinformation includes at least one of vital sign information, images, andmedical device use information.

Clause 26. The method of any clause herein, wherein the device-generatedinformation includes performance information; and

wherein generating the second biometric signature uses the performanceinformation.

Clause 27. The method of any clause herein, wherein generating the firstbiometric signature uses historical performance information.

Clause 28. The method of any clause herein, wherein the first biometricsignature includes a first kinesiological signature; and

wherein the second biometric signature includes a second kinesiologicalsignature.

Clause 29. A tangible, non-transitory computer-readable storage mediumstoring instructions that, when executed, cause a processor to:

receive device-generated information from a medical device;

generate a first biometric signature;

using the device-generated information, generate a second biometricsignature;

using the first biometric signature and the second biometric signature,generate a signature comparison;

using the signature comparison, generate a signature indicator; and

transmit the signature indicator.

Clause 30. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the device-generated information isgenerated by the medical device.

Clause 31. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein using the device-generated information,the instructions further cause the processor to determine device-basedmedical coding information; and

wherein generating the second biometric signature uses the device-basedmedical coding information.

Clause 32. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the instructions further cause theprocessor to receive electronic medical records pertaining to a user ofthe medical device; and

wherein generating the first biometric signature uses the electronicmedical records.

Clause 33. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the instructions further cause theprocessor to:

using the second biometric signature and an emergency biometricsignature, generate an emergency comparison;

using the emergency comparison, generate an emergency indicator; and

transmit the emergency indicator.

Clause 34. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the instructions further cause theprocessor to generate the emergency biometric signature.

Clause 35. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the device-generated information includesat least one of vital sign information, images, and medical device useinformation.

Clause 36. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the device-generated information includesperformance information; and

wherein generating the second biometric signature uses the performanceinformation.

Clause 37. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the device-generated information includesperformance information; and

wherein generating the second biometric signature uses the performanceinformation.

Clause 38. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein generating the first biometric signatureuses historical performance information.

Clause 39. The tangible, non-transitory computer-readable storage mediumof any clause herein, wherein the first biometric signature includes afirst kinesiological signature; and

wherein the second biometric signature includes a second kinesiologicalsignature.

Clause 40. A system for processing medical claims, comprising:

a processor configured to:

-   -   receive device-generated information from a medical device,        wherein the device-generated information includes performance        information;    -   generate a first biometric signature;    -   using the device-generated information, generate a second        biometric signature, wherein the second biometric signature uses        the performance information;    -   using the first and second biometric signatures, generate a        signature comparison;    -   using the signature comparison, generate a signature indicator;        and    -   transmit the signature indicator.

Clause 41. The system of any clause herein, wherein the device-generatedinformation is generated by the medical device.

Clause 42. The system of claim 1, wherein, using the device-generatedinformation, the processor is further configured to determinedevice-based medical coding information; and

wherein generating the second biometric signature uses the device-basedmedical coding information.

Clause 43. The system of any clause herein, wherein the processor isfurther configured to generate emergency biometric signature.

Clause 44. The system of any clause herein, wherein the device-generatedinformation includes at least one of vital sign information, images, andmedical device use information.

Clause 45. The system of any clause herein, wherein generating the firstbiometric signature uses historical performance information.

Clause 46. The system of any clause herein, wherein the first biometricsignature includes a first kinesiological signature; and

wherein the second biometric signature includes a second kinesiologicalsignature.

Clause 47. The system of any clause herein, wherein the signatureindicator indicates the first and second biometric signatures areidentical.

Clause 48. The system of any clause herein, wherein the signatureindicator indicates the first and second biometric signatures aredifferent.

Clause 49. The system of any clause herein, wherein the signatureindicator indicates a statistical measure specifying a degree ofsimilarities or differences between the first and second biometricsignatures.

Clause 50. A computer-implemented system for processing medical claims,comprising:

a processor configured to:

-   -   receive device-generated information from a medical device,        wherein the device-generated information includes performance        information;    -   generate a first biometric signature;    -   using the device-generated information, generate a second        biometric signature, wherein the second biometric signature uses        the performance information;    -   using the first and second biometric signatures, generate a        signature comparison;    -   using the signature comparison, generate a signature indicator;        and    -   transmit the signature indicator.

Clause 51. The computer-implemented system of any clause herein, whereinthe device-generated information is generated by the medical device.

Clause 52. The computer-implemented system of any clause herein,wherein, using the device-generated information, the processor isfurther configured to determine device-based medical coding information;and

-   -   wherein generating the second biometric signature uses the        device-based medical coding information.

Clause 53. The computer-implemented system of any clause herein, whereinthe processor is further configured to generate emergency biometricsignature.

Clause 54. The computer-implemented system of any clause herein, whereinthe device-generated information includes at least one of vital signinformation, images, and medical device use information.

Clause 55. The computer-implemented system of any clause herein, whereingenerating the first biometric signature uses historical performanceinformation.

Clause 56. The computer-implemented system of any clause herein, whereinthe first biometric signature includes a first kinesiological signature;and

wherein the second biometric signature includes a second kinesiologicalsignature.

Clause 57. A method for processing medical claims, comprising:

receiving device-generated information from a medical device, whereinthe device-generated information includes performance information;

generating a first biometric signature;

using the device-generated information, generating a second biometricsignature, wherein the second biometric signature uses the performanceinformation;

using the first and second biometric signatures, generate a signaturecomparison;

using the signature comparison, generate a signature indicator; and

transmitting the signature indicator.

Clause 58. The method of any clause herein, wherein the device-generatedinformation is generated by the medical device.

Clause 59. The method of any clause herein, further comprising, usingthe device-generated information, determining device-based medicalcoding information; and

-   -   wherein generating the second biometric signature uses the        device-based medical coding information.

No part of the description in this application should be read asimplying that any particular element, step, or function is an essentialelement that must be included in the claim scope. The scope of patentedsubject matter is defined only by the claims. Moreover, none of theclaims is intended to invoke 35 U.S.C. § 112(f) unless the exact words“means for” are followed by a participle.

The foregoing description, for purposes of explanation, use specificnomenclature to provide a thorough understanding of the describedembodiments. However, it should be apparent to one skilled in the artthat the specific details are not required to practice the describedembodiments. Thus, the foregoing descriptions of specific embodimentsare presented for purposes of illustration and description. They are notintended to be exhaustive or to limit the described embodiments to theprecise forms disclosed. It should be apparent to one of ordinary skillin the art that many modifications and variations are possible in viewof the above teachings.

The above discussion is meant to be illustrative of the principles andvarious embodiments of the present invention. Once the above disclosureis fully appreciated, numerous variations and modifications will becomeapparent to those skilled in the art. It is intended that the followingclaims be interpreted to embrace all such variations and modifications.

What is claimed is:
 1. A system for processing medical claims,comprising: a processor configured to: receive device-generatedinformation from a medical device, wherein the device-generatedinformation includes performance information; generate a first biometricsignature; using the device-generated information, generate a secondbiometric signature, wherein the second biometric signature uses theperformance information; using the first and second biometricsignatures, generate a signature comparison; using the signaturecomparison, generate a signature indicator; and transmit the signatureindicator.
 2. The system of claim 1, wherein the device-generatedinformation is generated by the medical device.
 3. The system of claim1, wherein, using the device-generated information, the processor isfurther configured to determine device-based medical coding information;and wherein generating the second biometric signature uses thedevice-based medical coding information.
 4. The system of claim 3,wherein the processor is further configured to generate emergencybiometric signature.
 5. The system of claim 1, wherein thedevice-generated information includes at least one of vital signinformation, images, and medical device use information.
 6. The systemof claim 1, wherein generating the first biometric signature useshistorical performance information.
 7. The system of claim 1, whereinthe first biometric signature includes a first kinesiological signature;and wherein the second biometric signature includes a secondkinesiological signature.
 8. The system of claim 1, wherein thesignature indicator indicates the first and second biometric signaturesare identical.
 9. The system of claim 1, wherein the signature indicatorindicates the first and second biometric signatures are different. 10.The system of claim 1, wherein the signature indicator indicates astatistical measure specifying a degree of similarities or differencesbetween the first and second biometric signatures.
 11. Acomputer-implemented system for processing medical claims, comprising: aprocessor configured to: receive device-generated information from amedical device, wherein the device-generated information includesperformance information; generate a first biometric signature; using thedevice-generated information, generate a second biometric signature,wherein the second biometric signature uses the performance information;using the first and second biometric signatures, generate a signaturecomparison; using the signature comparison, generate a signatureindicator; and transmit the signature indicator.
 12. Thecomputer-implemented system of claim 11, wherein the device-generatedinformation is generated by the medical device.
 13. Thecomputer-implemented system of claim 11, wherein, using thedevice-generated information, the processor is further configured todetermine device-based medical coding information; and whereingenerating the second biometric signature uses the device-based medicalcoding information.
 14. The computer-implemented system of claim 13,wherein the processor is further configured to generate emergencybiometric signature.
 15. The system of claim 11, wherein thedevice-generated information includes at least one of vital signinformation, images, and medical device use information.
 16. Thecomputer-implemented system of claim 11, wherein generating the firstbiometric signature uses historical performance information.
 17. Thesystem of claim 11, wherein the first biometric signature includes afirst kinesiological signature; and wherein the second biometricsignature includes a second kinesiological signature.
 18. A method forprocessing medical claims, comprising: receiving device-generatedinformation from a medical device, wherein the device-generatedinformation includes performance information; generating a firstbiometric signature; using the device-generated information, generatinga second biometric signature, wherein the second biometric signatureuses the performance information; using the first and second biometricsignatures, generate a signature comparison; using the signaturecomparison, generate a signature indicator; and transmitting thesignature indicator.
 19. The method of claim 18, wherein thedevice-generated information is generated by the medical device.
 20. Themethod of claim 18, further comprising, using the device-generatedinformation, determining device-based medical coding information; andwherein generating the second biometric signature uses the device-basedmedical coding information.